The Corporate Control Management is seeking an established associate to join the team as a Data Quality / Data Management Product Owner. In this role you should have a combination of deep Data Quality insights, strong analytics skill set across various complex data sets, foundational product development lifecycle experience, with experience in developing automated Data Quality dashboards and reporting solutions from design to implementation. In addition, you will have the opportunity to promote and ensure high-quality, fit-for-purpose data as part of data ingestion/movement strategies to the Cloud.
As a Data Management Product Owner/Analyst within the Controls Management Data Governance team, you will ensure the fitness of data for reporting. This includes managing the ingestion of data into the reporting platform and ensuring the implementation of all necessary data quality controls. Your role will also involve establishing data reconciliation, metadata registration, and data validation processes, as well as supporting the governance of outbound data feeds. You will be a key player in the Controls Management Controls Room, a Firmwide Reporting Utility that aims to standardize control-related data and enhance reporting efficiency and accuracy. This information warehouse provides reporting, visualization, and analytics capabilities, with the primary goal of improving control oversight and efficiency through the standardization and automation of operational risk reporting. You will also contribute to providing access to Firmwide aggregated information and generating business risk insights.
Job responsibilities
Demonstrate good understanding of data governance framework, data quality & data lineage Implement and support Data Quality (DQ) practices. Define and manage data validation rules/reconciliations for critical data elements and other core attributes by running complex SQL queries Govern and triage DQ Issues as it progresses through the lifecycle Discover and document data-lineage to trace the end-to-end data journey from point of creation to consumption Set up data profiling and DQ rules leveraging DQ tools like RDHP (Reference Data Hosting Platform), Collibra, Informatica and other emerging tools Leverage productivity tools such as Alteryx and visualization tools such as Tableau to analyze large dataset to draw inferences Collaborate & Build strong partnerships with Business stakeholders & Technology teams to support data quality efforts Define data quality rules for critical data elements based on the Firmwide dimensions and obtain approval from Data Owners Demonstrates Teamwork by collaborating with others to integrate ideas & achieve common goals Set up ingestion of data sources to AWS public cloud and ensure data matches between source and target Review data models to understand data concepts and relationships. Perform ad hoc analysis and data extracts using Databricks or Hue/ImpalaRequired qualifications, capabilities and skills
Quantitative background (BA/BS in Math, Statistics, Economics, Computer Science, Engineering) with 3+ years of experience working with technology partners to develop products Experience using Data Quality tools such as Informatica Data Quality (BDQ/IDQ), DQCS (Data Quality Control Services), AWS Glue or similar tools is experience required Experience implementing and supporting Data Quality (DQ) practices by running data profiling and interpreting profiling results for CDEs. Experience defining and managing data validation rules/reconciliations for critical data elements and other core attributes by running complex SQL queries Experience using analytics and visualization tools/libraries (Tableau, Alteryx, etc.) to distill findings into insightful analytical solutions for stakeholders Experience translating user requests to technology requirements using agile management tools like JIRA Experience working with large complex data sets, understanding algorithm, drawing conclusions, and reporting DQ findings Excellent written and verbal communications skills. Must be able to communicate with a wide variety of functional groups at various levels SQL, Excel and PowerPoint is a must have Flexible, adaptable to shifting priorities; able to work in a fast-paced, results driven environment Experience using metadata management tools such as Informatica/Collibra, RDHP and Jade CatalogPreferred qualifications, capabilities and skills
An understanding of the agile methodology Experience project managing small to large scale projects Experience working with internal control and risk management is a plus Strong background and understanding of big data and AWS Public Cloud environment and tools Enthusiastic, self-motivated, effective under pressure and willing to take personal responsibility/accountability Financial services industry background with specific experience in data analysis, DQ reporting or risk and controls